Fabric Lakehouse

Microsoft Fabric is an all-encompassing analytics solution designed to meet the diverse needs of enterprises. It offers a comprehensive suite of services that covers data engineering, data integration, data science, real-time analytics, and business intelligence, all seamlessly integrated into a single, user-friendly platform.

At the heart of Microsoft Fabric lies Fabric Lakehouse, a unified architecture that simplifies data management and analytics for organizations. This approach brings together various components and experiences to create a seamless, end-to-end environment for users.

The foundation of Fabric Lakehouse is built upon a Software as a Service (SaaS) model, offering a level of simplicity and integration that streamlines analytics processes. It amalgamates components from industry-leading tools like Power BI, Azure Synapse, and Azure Data Factory, presenting these components in tailored user interfaces to cater to specific tasks and personas.

Microsoft Fabric comprises several key components, each designed to excel in its respective area. These components include Data Engineering, which offers a powerful Spark platform for large-scale data transformation, and Data Factory, which combines Power Query with Azure Data Factory for seamless data integration. The Data Science component empowers users to build, deploy, and operationalize machine learning models, facilitating predictive insights. The Data Warehouse component stands out with its industry-leading SQL performance and scalability, offering independent scaling of compute and storage while natively storing data in the open Delta Lake format. Real-Time Analytics, designed for handling observational data, caters to the fastest-growing data category and works with semi-structured data in high volumes. Finally, Power BI, a leading Business Intelligence platform, ensures users can swiftly and intuitively access all data within Fabric for informed decision-making.

OneLake, an integral part of Fabric Lakehouse, serves as the foundational data lake. Also known as Microsoft Fabric Lake, it's built on Azure Data Lake Storage (ADLS) Gen2. OneLake provides a unified location for storing organizational data, regardless of whether users are professional developers or citizen developers. It simplifies the data storage and sharing process, eliminating the need for users to grasp intricate infrastructure concepts. It ensures data remains centralized and enforces policy and security settings uniformly.

In terms of organizational structure, OneLake is hierarchical, simplifying management across the organization. It spans across users, regions, and clouds, offering a single-pane-of-glass file-system namespace. Workspaces can be created within a tenant, which function similarly to folders, and lakehouses within these workspaces serve as collections of files, folders, and tables that represent a database over a data lake.

Microsoft Fabric's compute experiences, such as Data Engineering, Data Warehouse, Data Factory, Power BI, and Real-Time Analytics, are inherently connected to OneLake, making data access and processing a seamless experience. Users can mount existing Platform as a Service (PaaS) storage accounts into OneLake instantly, facilitating data sharing without the need for migration or duplication.

In conclusion, Fabric Lakehouse embodies the unified data management and analytics architecture within Microsoft Fabric, offering a simplified and cohesive approach to data storage, processing, and analysis, which is particularly beneficial for enterprises seeking an efficient and user-friendly solution.

Azure Synapse Analytics

data types we support

bigint (int8)
int (integer, int4)
smallint (int2)
decimal (dec, numeric, fixed)
double precision (double, float8)
real (float4)
char (bpchar, character)
varchar (character varying)
time (timetz, time without time zone)
timestamp (timestamp without time zone, timestamp(2) without time zone)
timestamptz (timestamp with time zone, timestamp(2) with time zone)
Large objects
boolean (bool)
varbit (bit varying)